Stock trend prediction is regarded as a challenging task. Recently many researches have
shown that a successful feature selection method can improve the prediction accuracy of …

This paper suggests evolving linear models as a powerful alternative for online forecasting
of synchronous time series. First, using a priori knowledge of an expert, all known possible …

Abstract Kernel methods (Cristianini and Shawe-Taylor 2000; Herbrich 2002; Schölkopf and
Smola 2002; Shawe-Taylor and Cristianini 2004) can be regarded as machine learning …

Week-ahead load forecasting is essential in the planning activities of every electricity
production and distribution company. This paper proposes the application of principal …

Graduates of computer science degree programs are increasingly being asked to maintain
large, multi-threaded software systems; however, the maintenance of such systems is …

Abstract Support Vector Regression (SVR) has been applied successfully to financial time
series prediction recently. In SVR, the ε-insensitive loss function is usually used to measure …

Neste trabalho é realizado um estudo sistemático para a resolução do problema de
previsão de séries temporais com a utilização de técnicas de Inteligência Artificial …

Due to the complexity of real task for learning, the learning algorithms based on ERM
(empirical risk minimization) principle always have good fit for the training samples, but bad …

Sleep is an important part of life, and sleep position recognition is an important indicator
which reflects sleep quality, warns diseases and prevents pressure sores. Actually, sleep …

With the development of economy, the stock market of China is booming rapidly. In recent
years, a method called multiple sine functions extraction (MSFE) has been proposed, eg, to …